APPLICATION OF ACOUSTIC METHODS IN RESEARCHES OF THE BOTTOM SEDIMENT DYNAMICS

Author(s):  
Б. Дивинский ◽  
B. Divinskiy ◽  
И. Грюне ◽  
I. Gryune ◽  
Р. Косьян ◽  
...  

Acoustic methods belong to contactless measurement means, possess high spatial and time resolution. Thus, the use of multifrequency allows directly profile both concentration and granulometric structure of the suspended substances. In 2008 in the Big Wave Flume (Hanover, Germany) by efforts of the Russian and German scientists there have been carried out the experiment on studying the bottom material suspension laws under the influence of irregular waves. The Aquascat 1000 acoustic back scattering sensor (ABS) manufactured by British company Aquatec (www.aquatecsubsea.com), equipped by a three-frequency transmitter with frequencies 1,0, 2,0 and 3,84 MHz, has been set on distance of 0,75 m from the bottom and 111 m from wave generator at the total depth of 3,2 m. Several dozen series of measurements at various parameters of surface waves have been carried out. The general picture of suspension is so that the external dynamic influence (currents, wave movements, turbulence, gravitation forces) creates a non-uniform field (gradient) of the suspended particles and in most cases due to this the average size of particles undergoes to the spatial-time variations. For this reason while defining the mass concentration of suspended sediment, using the single frequency transmitter there is necessity for numerous definition of the suspension granulometric structure what by isn’t always possible. If two and more frequencies are used the observed results comparison can give the information on average diameters of particles and on that basis the calculation of suspended sediment concentration is possibleLet's emphasize the basic advantages of back scattering acoustic gauges usage: – Obtaining the particles sizes and concentration distribution profiles is possible; – The initial granulometric structure of bottom sediments can be unknown (at use of several frequencies). The following can be referred to some lacks of the device: – The system should be calibrated in laboratory conditions; – In a positive feedback conditions the iterative computing process can converge to zero or to infinity. In this case experiments with a variation of carrier frequencies chosen for the analysis allow partially solve the problem (say experiments with different frequencies pairs, as 2/1 of MHz or 4/2 MHz).

1986 ◽  
Vol 1 (20) ◽  
pp. 79 ◽  
Author(s):  
Hans H. Dette ◽  
Klemens Uliczka

Wave-induced currents and sediment concentrations in suspension across the surf zone were investigated at prototype scale in the BIG WAVE FLUME in Hannover for combined beach and dune profiles as well during the development phase until quasi-equilibrium stage as after beach equilibrium conditions had been reached. The selected initial profiles were partly investigated in repeated tests with regular and irregular waves. Based upon the obtained experimental data a comparison is presented between the measured and calculated landward displacement of sediment volume through a selected point on the beach into seaward areas. The discrepancies in between the results for measured profile change and for calculated sediment transport volume derived from vertical current and suspension distributions are discussed.


2013 ◽  
Vol 11 (4) ◽  
pp. 457-466

Artificial neural networks are one of the advanced technologies employed in hydrology modelling. This paper investigates the potential of two algorithm networks, the feed forward backpropagation (BP) and generalized regression neural network (GRNN) in comparison with the classical regression for modelling the event-based suspended sediment concentration at Jiasian diversion weir in Southern Taiwan. For this study, the hourly time series data comprised of water discharge, turbidity and suspended sediment concentration during the storm events in the year of 2002 are taken into account in the models. The statistical performances comparison showed that both BP and GRNN are superior to the classical regression in the weir sediment modelling. Additionally, the turbidity was found to be a dominant input variable over the water discharge for suspended sediment concentration estimation. Statistically, both neural network models can be successfully applied for the event-based suspended sediment concentration modelling in the weir studied herein when few data are available.


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